The present application relates to methods for selecting or capturing image data in response to a trigger signal, and more particularly, to a vehicle identification method in which an image of a license plate on a vehicle moving through a field of view of an imaging sensor is captured in response to a trigger signal indicating either the front or rear surface of the vehicle is ideally located within a license plate observation area for acquisition of a license plate image.
Vehicle license plate recognition (LPR) image-processing technology is commonly utilized to capture identifying information from an image of a vehicle license plate. The technology is often used in a variety of security and traffic control or monitoring applications. A typical LPR system includes at least one imaging sensor for acquiring images of a vehicle, and an image processing system for evaluating the acquired images to identify visible license plates and extract relevant alpha-numerical data. The LPR system may further include an illumination system for use when ambient light is insufficient to illuminate the vehicle and license plate surfaces, and a network connection for exchanging data with one or more remote systems. The image processing system may be implemented as a hardware or software component associated with the imaging sensor, or may function as an independent processing system in communication with the imaging sensor.
A variety of techniques are known for triggering the acquisition of images by an imaging sensor, or the selection of a specific image frames in a stream of sequential images acquired continuously by the imaging sensor. In an automotive license plate recognition context, these techniques may include the interruption of optical beams by a passing vehicle, activation of pressure or inductive sensors on a roadway surface triggered by a passing vehicle, or the use of motion sensors to detect the movement of a passing vehicle. Some systems, known as edge cameras, continuously acquire a stream of images representative of a field of view, and apply a brute force image analysis approach to evaluate each individual image to identify the presence of a license plate from which license plate data can be extracted. This type of approach requires an expensive high-speed image processing system to enable every acquired image to be evaluated for license plate information. A significant amount of time and resources are wasted processing images in which no vehicle or license plate is present.
When acquiring an image of a vehicle for the purpose of identifying license plate data, it is useful to acquire the image when the front or rear portion of the vehicle is within a selected region of the imaging sensor's field of view. This ensures that a license plate, if present on the vehicle, can be adequately resolved within the acquired image, enabling appropriate image processing to extract vehicle identifying data. Systems which rely upon the detection of a vehicle entering a field of view lack the ability to accommodate vehicles of varying wheelbases when attempting to capture images of the rear surfaces of the vehicle. For example a short wheelbase vehicle, upon triggering an interrupt signal from an optical beam, may be too far from the imaging sensor, while the rear surfaces of a long wheelbase vehicle may not yet have passed fully into the field of view of the imaging sensor upon triggering the interrupt signal. Inductive sensors and pressure sensor experience similar issues with an inability to identify the leading or trailing edge of the vehicle to any degree of precision.
Accordingly, it would be advantageous to provide an efficient and low-cost method for triggering an imaging sensor to capture an image, or to select an image frame from a video stream for further evaluation, only when the front or rear surface of a passing vehicle is at an ideal location, or within an ideal observation region, for acquisition of license plate data within the imaging sensor's field of view.